Diagnostic utility of clinical indicator data to identify neuropathic pain in low back related leg pain: A systematic review

Physiotherapy ◽  
2021 ◽  
Vol 113 ◽  
pp. e173-e174
Author(s):  
J. Mistry ◽  
N. Heneghan ◽  
T. Noblet ◽  
D. Falla ◽  
A. Rushton
Keyword(s):  
Systematic Review ◽  
Neuropathic Pain ◽  
Leg Pain ◽  
Diagnostic Utility ◽  
Low Back ◽  
Clinical Indicator ◽  
Indicator Data

scholarly journals Diagnostic utility of patient history, clinical examination and screening tool data to identify neuropathic pain in low back-related leg pain: protocol for a systematic review

BMJ Open ◽  
2019 ◽  
Vol 9 (11) ◽  
pp. e033187 ◽  
Author(s):  
Jai Mistry ◽  
Nicola R Heneghan ◽  
Timothy Noblet ◽  
Deborah Falla ◽  
Alison Rushton
Keyword(s):  
Systematic Review ◽  
Neuropathic Pain ◽  
Diagnostic Accuracy ◽  
Clinical Examination ◽  
Screening Tool ◽  
Meta Analysis ◽  
Leg Pain ◽  
Diagnostic Utility ◽  
Low Back ◽  
Patient History

IntroductionNeuropathic low back-related leg pain (LBLP) can be a challenge to healthcare providers to diagnose and treat. Accurate diagnosis of neuropathic pain is fundamental to ensure appropriate intervention is given. However, to date there is no gold standard to diagnose neuropathic LBLP. Patient examination guidelines and screening tools have been developed and validated for the purpose of diagnosing neuropathic pain in LBLP; however, there has been no systematic review conducted to compare the diagnostic validity of these methods. Therefore, this systematic review will investigate the diagnostic utility of patient history, clinical examination and screening tool data to identify neuropathic pain in LBLP.Methods and analysisThis protocol is informed and reported in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis-Protocols. CINAHL, EMBASE, MEDLINE, Web of Science, Cochrane Library, AMED, Pedro, PubMed, key journals and grey literature will be searched rigorously to find diagnostic accuracy studies investigating patient examination data to identify neuropathic pain in LBLP patients. Two independent reviewers will conduct the search, extract the data and assess risk of bias for included studies using the Quality Assessment of Diagnostic Accuracy Studies 2 tool. The overall quality of included studies will be evaluated using Grading of Recommendations, Assessment, Development and Evaluation guidelines. A meta-analysis will be conducted if deemed appropriate. Otherwise, a narrative synthesis will be conducted.Ethics and disseminationNo research ethics is required for this systematic review since patient data will not be collected. This review will help to inform healthcare professionals and researchers on the most effective means in which to diagnose neuropathic pain in LBLP. Results of this review will be submitted for publication in a peer-review journal and conference presentations.PROSPERO registration numberCRD42019140861

The Effectiveness of Spinal Cord Stimulation for the Treatment of Axial Low Back Pain: A Systematic Review with Narrative Synthesis

Pain Medicine ◽  
2020 ◽  
Vol 21 (11) ◽  
pp. 2699-2712
Author(s):  
Aaron Conger ◽  
Beau P Sperry ◽  
Cole W Cheney ◽  
Taylor M Burnham ◽  
Mark A Mahan ◽  
...  
Keyword(s):  
Systematic Review ◽  
Spinal Cord ◽  
Low Back Pain ◽  
High Frequency ◽  
Low Frequency ◽  
Leg Pain ◽  
Low Back ◽  
Level 1 ◽  
Pain Improvement ◽  
Quality Evidence

Abstract Objective Determine the effectiveness of spinal cord stimulation (SCS) for the treatment of axial low back pain (LBP) with or without leg pain. Design Systematic review. Subjects Persons aged ≥18 with axial LBP with or without accompanying leg pain. Intervention Traditional low-frequency, burst, or high-frequency SCS. Comparison Sham, active standard of care treatment, or none. Outcomes The primary outcome was ≥50% pain improvement, and the secondary outcome was functional improvement measured six or more months after treatment intervention. Methods Publications in PubMed, MEDLINE, and Cochrane databases were reviewed through September 19, 2019. Randomized or nonrandomized comparative studies and nonrandomized studies without internal controls were included. The Cochrane Risk of Bias Tool and GRADE system were used to assess individual study characteristics and overall quality. Results Query identified 262 publications; 17 were suitable for inclusion. For high-frequency SCS, the only level 1 study showed that 79% (95% confidence interval = 70–87%) of patients reported ≥50% pain improvement. For low-frequency SCS, the only level 1 study reported no categorical data for axial LBP-specific outcomes; axial LBP improved by a mean 14 mm on the visual analog scale at six months. Meta-analysis was not performed due to study heterogeneity. Conclusions According to GRADE, there is low-quality evidence that high-frequency SCS compared with low-frequency SCS is effective in patients with axial LBP with concomitant leg pain. There is very low-quality evidence for low-frequency SCS for the treatment of axial LBP in patients with concomitant leg pain. There is insufficient evidence addressing the effectiveness of burst SCS to apply a GRADE rating.

scholarly journals Clinical indicators to identify neuropathic pain in low back-related leg pain: protocol for a modified Delphi study

BMJ Open ◽  
2020 ◽  
Vol 10 (2) ◽  
pp. e033547 ◽  
Author(s):  
Jai Mistry ◽  
Deborah Falla ◽  
Tim Noblet ◽  
Nicola R Heneghan ◽  
Alison B Rushton
Keyword(s):  
Neuropathic Pain ◽  
Delphi Study ◽  
A Priori ◽  
Healthcare Providers ◽  
Leg Pain ◽  
Eligibility Criterion ◽  
Low Back ◽  
Clinical Indicators ◽  
Modified Delphi ◽  
Ethical Approval

IntroductionNeuropathic low back-related leg pain (LBLP) can be a challenge to healthcare providers to diagnose and treat. Accurate diagnosis of neuropathic pain is fundamental to ensure appropriate intervention is given. However, to date there is no gold standard to diagnose neuropathic LBLP. A Delphi study will therefore be conducted to obtain an expert-derived consensus list of clinical indicators to identify a neuropathic component to LBLP.Methods/analysisIncluded participants will be considered experts within the field as measured against a predefined eligibility criterion. Through an iterative multistage process, participants will rate their agreement with a list of clinical indicators and suggest any missing clinical indicators during each round. Agreement will be measured using a 5-point Likert scale. Descriptive statistics will be used to measure agreement; median, IQR and percentage of agreement. A priori consensus criteria will be defined for each round. Data analysis at the end of round three will enable a list of clinical indicators to be derived.Ethics and disseminationEthical approval was gained from the University of Birmingham (ERN_19-1142). On completion of the study, findings will be disseminated in a peer-reviewed journal and presented at relevant conferences.

scholarly journals Clinical indicators to identify neuropathic pain in low back related leg pain: a modified Delphi study

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Jai Mistry ◽  
Deborah Falla ◽  
Tim Noblet ◽  
Nicola R. Heneghan ◽  
Alison Rushton
Keyword(s):  
Neuropathic Pain ◽  
Delphi Study ◽  
Leg Pain ◽  
Complete Agreement ◽  
Low Back ◽  
Eligibility Criteria ◽  
Clinical Indicators ◽  
Modified Delphi ◽  
Coefficient Of Concordance ◽  
Kendall’S W

Abstract Background Neuropathic pain (NP) is common in patients presenting with low back related leg pain. Accurate diagnosis of NP is fundamental to ensure appropriate intervention. In the absence of a clear gold standard, expert opinion provides a useful methodology to progress research and clinical practice. The aim of this study was to achieve expert consensus on a list of clinical indicators to identify NP in low back related leg pain. Methods A modified Delphi method consisting of three rounds was designed in accordance with the Conducting and Reporting Delphi Studies recommendations. Recruitment involved contacting experts directly and through expressions of interest on social media. Experts were identified using pre-defined eligibility criteria. Priori consensus criteria were defined for each round through descriptive statistics. Following completion of round 3 a list of clinical indicators that achieved consensus were generated. Results Thirty-eight participants were recruited across 11 countries. Thirty-five participants completed round 1 (92.1%), 32 (84.2%) round 2 and 30 (78.9%) round 3. Round 1 identified consensus (Kendall’s W coefficient of concordance 0.456; p < 0.001) for 10 clinical indicators out of the original 14, and 9 additional indicators were added to round 2 following content analysis of qualitative data. Round 2 identified consensus (Kendall’s W coefficient of concordance 0.749; p < 0.001) for 10 clinical indicators out of 19, and 1 additional indicator was added to round 3. Round 3 identified consensus for 8 indicators (Kendall’s W coefficient of concordance 0.648; p < 0.001). Following completion of the third round, an expert derived consensus list of 8 items was generated. Two indicators; pain variously described a burning, electric shock like and/or shooting into leg and pain in association with other neurological symptoms (e.g. pins and needles, numbness, weakness), were found to have complete agreement amongst expert participants. Conclusions Good agreement was found for the consensus derived list of 8 clinical indicators to identify NP in low back related leg pain. This list of indicators provide some indication of the criteria upon which clinicians can identify a NP component to low back related leg pain; further research is needed for stronger recommendations to be made.

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